Modular imaging system

ABSTRACT

A modular imaging system includes an antenna panels, a sensor, and at least one data processor. The antenna panels include an array of antenna elements including at least two antenna elements separated by a spacing more than a half wavelength. The plurality of antenna panels are configurable to be spatially arranged and oriented with respect to one another to measure radar returns of an observation domain for a target. The sensor has a field of view overlapping the observation domain and for measuring an image. The at least one data processor forms part of at least one computing system and is adapted to receive data characterizing the optical image and the radar returns, determine a spatial location of the target, and construct a radar return image of the target using a sparsity constraint determined from the spatial location of the target. Related apparatus, systems, techniques, and articles are also described.

RELATED APPLICATIONS

This application claims priority under 35 U.S.C. § 119 to U.S.Provisional patent application No. 62/142,730 filed Apr. 3, 2015, theentire contents of which is hereby expressly incorporated by referenceherein.

TECHNICAL FIELD

The subject matter described herein relates to a modular imaging system,for example, with multiple antenna panels that can be modularlyassembled.

BACKGROUND

Airport security attempts to prevent any threats or potentiallydangerous situations from arising or entering the country. Some existingradio frequency (RF) imaging systems (such as those utilized by airportsecurity for passenger screening) are large, expensive, and requireindividuals to remain stationary while an antenna rotates around thestationary individual to capture an image. In addition, these existingRF imaging systems may be limited to checkpoint security screening andmay not reconfigure for other applications.

SUMMARY

In an aspect, a modular imaging system includes a plurality of antennapanels, a sensor and at least one data processor. The plurality ofantenna panels include an array of antenna elements including at leasttwo antenna elements separated by a spacing more than a half wavelength.The plurality of antenna panels are configurable to be spatiallyarranged and oriented with respect to one another to measure radarreturns of an observation domain for a target. The sensor has a field ofview overlapping the observation domain and for measuring an image. Theat least one data processor forms part of at least one computing systemand is adapted to receive data characterizing the optical image and theradar returns, determine a spatial location of the target using the datacharacterizing the image, and construct a radar return image of thetarget using a sparsity constraint determined from the spatial locationof the target.

In another aspect, data characterizing radar returns measured by aplurality of antenna panels comprising an array of antenna elementsincluding at least two antenna elements separated by a spacing more thana half wavelength is received. The plurality of antenna panels areconfigurable to be spatially arranged and oriented with respect to oneanother to measure radar returns of an observation domain for a target.Data characterizing an image containing the observation domain andmeasured by a sensor having a field of view overlapping with theobservation domain is received. A spatial location of the target isdetermined using the data characterizing the image. A radar return imageof the target is constructed using a sparsity constraint determined fromthe spatial location of the target.

One or more of the features disclosed herein including the followingfeatures can be included in any feasible combination. For example, abase station can be included, the base station to at least receive theradar returns from the plurality of antenna panels and generate the datacharacterizing the radar returns as in-phase and quadrature data. The atleast one data processor forming part of at least one computing systemcan be further adapted to detect for a presence of threat objects in theradar return image. A display can be included. The at least one dataprocessor forming part of the at least one computing system can befurther adapted to render, in the display, characterizations of thedetected threat objects. The spatial location of the target can defineempty voxels and voxels in which the target is present. The plurality ofantenna panels can be configurable to be spatially arranged and orientedwith respect to one another based on an intended application. Theplurality of antenna panels can be configurable to be spatially arrangedvertically adjacent to inspect targets moving through the observationdomain.

Data characterizing the radar returns can be generated as in-phase andquadrature data and by a base station receiving the radar returns fromthe plurality of antenna panels. A presence of threat objects can beautomatically detected for in the radar return image. Characterizationsof the detected threat objects can be rendered in a display. The spatiallocation of the target can define empty voxels and voxels in which thetarget is present. The plurality of antenna panels can be configurableto be spatially arranged and oriented with respect to one another basedon a given application. The plurality of antenna panels can beconfigurable to be spatially arranged vertically adjacent to inspecttargets moving through the observation domain.

The plurality of antenna panels can include four approach panels andfour rearward panels. The four approach panels can be arrangedvertically with respect to one another and coplanar in a first plane.The four rearward panels can be arranged vertically with respect to oneanother and coplanar in a second plane. An angle between the first planeand the second plane can be between 10 degrees and 170 degrees. Theangle between the first plane and the second plane can be between 60degrees and 120 degrees. The four approach panels can span a verticaldistance less than 160 centimeters and each panel's vertical dimensioncan be between 20 and 30 centimeters. The plurality of antenna panelscan further include a second set of four approach panels and a secondset of four rearward panels, with a pass-through region between the fourapproach panels and the second set of approach panels.

A housing can be included. The housing can have a first hinge to foldthe housing, the housing coupled to the plurality of antenna panels, theplurality of antenna panels including four panels coplanar in a firstplane. The plurality of antennas can further include a fifth panelcoupled to the housing with a second hinge. The system can becollapsible by folding the housing using the first hinge so that eachpanel in the plurality of antenna panels is enclosed by the housing.When the housing is in a closed position, a largest dimension of thehousing can be less than 50 centimeters, and a second dimension of thehousing can be between 27 centimeters and 40 centimeters.

The plurality of antenna panels can include at least nine coplanarpanels in a row and column arrangement, each panel separated from aneighboring panel by between 4 and 8 centimeters.

The plurality of antenna panels can include a first set of two approachpanels and a second set of two approach panels. The first set of twoapproach panels can be arranged vertically with respect to one anotherand coplanar in a first plane. The second set of two approach panelsarranged vertically with respect to one another and coplanar in a secondplane. An angle between the first plane and the second plane can bebetween 100 and 170 degrees. The two approach panels in the first setcan be separated vertically by between 30 and 60 centimeters.

Non-transitory computer program products (i.e., physically embodiedcomputer program products) are also described that store instructions,which when executed by one or more data processors of one or morecomputing systems, causes at least one data processor to performoperations herein. Similarly, computer systems are also described thatmay include one or more data processors and memory coupled to the one ormore data processors. The memory may temporarily or permanently storeinstructions that cause at least one processor to perform one or more ofthe operations described herein. In addition, methods can be implementedby one or more data processors either within a single computing systemor distributed among two or more computing systems. Such computingsystems can be connected and can exchange data and/or commands or otherinstructions or the like via one or more connections, including but notlimited to a connection over a network (e.g. the Internet, a wirelesswide area network, a local area network, a wide area network, a wirednetwork, or the like), via a direct connection between one or more ofthe multiple computing systems, etc.

The details of one or more variations of the subject matter describedherein are set forth in the accompanying drawings and the descriptionbelow. Other features and advantages of the subject matter describedherein will be apparent from the description and drawings, and from theclaims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a system block diagram of an example modular imaging systemincluding multiple antenna panels that can be modularly assembled,scaled, and arranged;

FIG. 2 is an example layout of an antenna panel that contains sparselydistributed antenna elements;

FIG. 3A is an illustration of antenna panels arranged in a walk-thrucheckpoint screening concept of operation;

FIG. 3B is a top view of the antenna panel configuration illustrated inFIG. 3A;

FIG. 4 is an illustration of four antenna panels arranged as a largeflat panel;

FIG. 5 is a processing block diagram illustrating processing steps ofvarious components of the example modular imaging system;

FIG. 6 is a process flow diagram illustrating a process of constructinga radar return image from data measured by a plurality of antennapanels;

FIG. 7 illustrates further additional concepts of operation;

FIGS. 8A, 8B, and 8C illustrate the security checkpoint configuration705 in more detail;

FIG. 9A illustrates a variation of the security checkpoint configurationthat can covertly integrate into a doorway;

FIG. 9B illustrates another variation of the security checkpointconfiguration in which two panels are used overtly to screen individualsat an access point;

FIGS. 10A and 10B illustrate another variation of the securitycheckpoint configuration in which the panels are arrange insubstantially cylindrical arrangement to improve inspection viewingangles;

FIGS. 11A-D illustrate a field access/portable arrangement in moredetail;

FIGS. 12A-C illustrate several implementations of a pass-by areaconfiguration;

FIGS. 13A and 13B illustrate dimensions of the example implementationillustrated in FIG. 12A; and

FIGS. 14A-C illustrates several views of an access and chokepointconfiguration.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

The current subject matter can include an RF imaging system includingmultiple antenna panels that can be modularly assembled, scaled, andindependently arranged based on an intended application. Moreover, theRF imaging system can include an optical sensor to provide forcompressed sensing to reduce the amount of data acquired and processedthereby reducing the RF imaging system's size and cost requirements.

The antenna panels can be connected to a base station for dataprocessing, which can be connected to a computing device for automaticimage generation, threat detection, and viewing of images. The systemcan detect threats, such as knives, guns, explosives, and the like,carried on an individual. Each antenna panel can act as a building blockof a whole system such that controlling the number of antenna panels andtheir orientation with respect to an observational domain allows thesystem to be configured for different applications.

In addition, each antenna panel can include a sparse array of antennaelements enabling images to be acquired using compressive sensingthereby reducing the amount of data acquired, which, in turn, reducesthe amount of data that must be processed. A sensor, such as a videocamera, can be included to determine a target's spatial location forenforcing compressed sensing sparsity constraints.

FIG. 1 is a system block diagram of an example modular imaging system100 including multiple antenna panels 105 _(i) (i=1, 2, . . . , n) thatcan be modularly assembled, scaled, and arranged; a data acquisitionsystem (DAS) panel 110 _(i) (i=1, 2, . . . , n) for controlling theantennas across the multiple antenna panels 105 _(i) and digitizing rawradar return data specific to itself; a DAS base station 115 foraggregating the digital data from multiple DAS panels 110 _(i); a RFBase Station 160 for driving antenna panels 105 _(i); a processingsystem 120 for analyzing the radar returns; a display 155 for providingoutput; and a Base to Base board 165 for interfacing the RF Base Station160 to the processing system 120. The example modular imaging system 100can include an optical sensor 125.

Each antenna panel 105 _(i) includes antenna elements that are sparselydistributed across the face of the antenna panel 105 _(i) to enablecompressed sensing of observation domain 107. Antenna elements can beconsidered sparsely distributed if a spacing of more than ahalf-wavelength (of an operating frequency) separates the elements. FIG.2 is an example layout of an antenna panel 105 _(i) that enablescompressed sensing. For any arbitrarily sized and shaped panel, thelayout and position of transmitters 205 and receivers 210 can bedetermined through numerical optimization methods (e.g., Monte-Carlomethods) by simulations using the criterion of: (1) maximally flatsingular value decomposition (SVD) for a resulting measurement matrix(e.g., measures the uniqueness of all measurements); (2) maximumdistance between effective monostatic sensor locations (e.g., center ofmass for every combination of transmitter and receiver); and (3) noviolations of physical board dimensions and RF layout considerations(e.g., no overlapping antennas, and transmitters and receivers confinedto opposite parts of the board). The layout and position of transmitters205 and receivers 210 can be represented by inter-panel effective sensorlocations 215, which can include the effective Mono-Static transmit,receive 3D spatial location of a trace.

In the example layout of an antenna panel 105 _(i) illustrated in FIG.2, each antenna panel 105 _(i) is a 27.6 cm×20.0 cm panel including 12transmitting antennas 205 and 12 receiving antennas 210 that can beselected and controlled independently (e.g., to transmit/receive),although other configurations are possible. The antennas can be shapedand located structures printed on the front surface of a multi-layerprinted circuit board assembly (PCBA). In an implementation, the modularimaging system's 100 transmit operating frequencies are between 24 and29.5 GHz (millimeter wave signals). In another implementation, themodular imaging system's 100 transmit operating frequencies include 60GHz. In an implementation, during operation a single panel system canserially generate 12 swept frequency traces, 1 at each transmitter, oneat a time. For each transmitter frequency sweep, the echoed signal canbe received on all 12 receivers in parallel and compared against thetransmitted signal (e.g., Local Oscillator from RF Base 160) therebyrecording 144 transmit-receive Bi-Static Antenna Pair FMCW traces. Eachtrace's range information is relative to the “mid-point of the line”between that trace's associated transmitting and receiving antennas. Fora two panel system there are 2 panels*12 transmitters per panel*2panela*12 receivers per panel resulting in 576 transmit receive pairs.For N panels there are N*N*12*12 pairs. The number of pairs increasewith the square of the number of panels. There is a rapid increase inspatial diversity of antenna locations as a function of the number ofpanels included in a system.

In addition, antenna panels 105 _(i) can be arranged in variousconfigurations and orientations with respect to one another toilluminate an observational domain (OD) 107. Moreover, the system iscapable of having an expandable number of antenna panels 105 _(i). Thenumber, configuration, and orientations of the antenna panels 105 _(i)can define customizable ODs based on an intended application. In otherwords, the modular imaging system 100 can support multiple concepts ofoperation. For example, FIG. 3A is an illustration of antenna panels 105_(i) arranged in a walk-thru checkpoint screening concept of operationand FIG. 3B is a top view of the antenna panels 105 _(i). Sixteenantenna panels 105 _(i) (i=1, 2, . . . , 16) are spatially arranged ingroups of four that are vertically adjacent (e.g., in a stackedconfiguration) and oriented with respect to one another to illuminate anOD 107 having two regions. More specifically, the antenna panels 105_(i) are attached to one of two posts 305. Individuals or other targetscan walk between the posts 305 thereby moving through the OD 107regions. By having individuals move through the OD 107 while the modularimaging system 100 is configured as illustrated in FIGS. 3A and 3B, themodular imaging system can illuminate both the front, sides, and rear ofthe target, and generate one or more images of the target.

Additional concepts of operation are possible. For example, FIG. 4 is anillustration of four antenna panels 105 _(i) arranged as a large flatpanel 400. The four antenna panels 105 _(i) can be oriented toilluminate an intended OD (e.g., to scan individuals walking past). Theantenna panels 105 _(i) can be arranged to illuminate the subject beingscreened, eliminating blind spots, and thereby improving overalldetection performance with a lower false alarm rate.

FIG. 7 illustrates further additional concepts of operation. Asdescribed more fully with reference to FIGS. 8-14, the antenna panels105 _(i) are arranged in a security checkpoint configuration at 705; ina field access/portable arrangement at 710; in a pass-by areaconfiguration at 715; and an access and chokepoint configuration at 720.

FIGS. 8A, 8B, and 8C illustrate the security checkpoint configuration705 in more detail. FIG. 8A is a cross-sectional diagram, FIG. 8B is afront view, and FIG. 8C is a side perspective view illustrating thesecurity checkpoint configuration. The security checkpoint configurationillustrated in FIG. 8A-C has two posts, each post having four approach(or forward facing) panels arranged vertically with respect to oneanother and four rearward panels arranged vertically with respect to oneanother. Each grouping of four panels is referred to as a set of panels.The approach panels in a given set are substantially coplanar in a firstplane (e.g., the face of the panels have substantially parallel normal).The rearward facing panels in a given set are substantially coplanar ina second plane. A pass-through region between the two posts (e.g., thefirst set of four approach panels and the second set of approach panels)allows for inspection of individuals or other targets passing throughthe posts.

In some implementations, the angle of the first plane a as measured to atransverse axis 815 can vary between 10 and 85 degrees. In an exampleimplementation, the angle α is 50 degrees. An angle of the second planecan similarly be between 10 and 85 degrees. Thus, an angle between thefirst plane and the second plane can be between 10 degrees and 170degrees, 60 and 120 degrees, and in the example implementation, theangle between the first plane and the second plane is 110 degrees. Bycontrolling the angle of the antenna panels, the observation domain canbe controlled.

Inter-panel spacing 805 in the vertical direction can vary and in anexample implementation is 16.8 cm. Thus, with the example panelsdescribed above (in which each panel's vertical dimension is between 20and 30 centimeters) and in the security checkpoint panel configuration,the four approach panels span a vertical distance less than 160centimeters. Inter-panel offset 810 can be 2.9 cm, which can allow forimproved resolution of the observational domain.

FIG. 9A illustrates a variation of the security checkpoint configurationin which four panels 105 _(i) (two on each side) are used (for approachfacing and/or rearward facing) and can covertly integrate into adoorway. Thus, the current subject matter can provide for covertmonitoring and screening of individuals as they pass through a doorway,which serves as a natural checkpoint. FIG. 9B illustrates anothervariation of the security checkpoint configuration in which two panelsare used overtly to screen individuals at an access point, for example,a turnstile for admitting individuals to public transportation, eventspace, or to a building. The current subject matter can scan anindividual and only authorize admittance if no threats are detected.

FIGS. 10A and 10B illustrates another variation of the securitycheckpoint configuration in which the panels 105 _(i) are arrange insubstantially cylindrical arrangement to improve inspection viewingangles. The security checkpoint configuration is shown with (FIG. 10A)and without (FIG. 10B) a traditional metal detector 1005.

FIGS. 11A, 11B and 11C illustrate a field access/portable arrangement710 in more detail. The field access/portable arrangement 710 includes ahousing 1105 having a first hinge 1110 to fold the housing 1105. Thehousing 1105 is coupled to four antenna panels 105 _(i), which arecoplanar when the housing is open. The field access/portable arrangementis collapsible by folding the housing 1105 using the first hinge 1110 sothat each panel 105 _(i) is contained or enclosed by the housing.

Inter-panel spacing 1120 and 1125 can vary and in an exampleimplementation can be 1.2 cm and 8.9 cm, respectively. Thus, with theexample panels described above (in which each panel's vertical dimensionis between 20 and 30 centimeters) and in the field access portablearrangement 710, the four panels span a first distance (e.g., height orwidth) that is less than 50 centimeters, and span a second distance(e.g., width or height, respectively) of the housing 1105 of less than40 centimeters.

The housing 1105 can fold into a brief-case-like shape for portability.For example, in an example implementation, when the housing 1105 isclosed, a largest dimension (e.g., length) of the housing can be lessthan 50 centimeters, and a second dimension (e.g., height) of thehousing is between 27 centimeters and 40 centimeters.

As illustrated in FIG. 11D, the housing 1105 can further includeadditional hinges 1115 coupling additional antenna panels 105 _(i) tothe housing 1105.

FIG. 12A-C illustrates several implementations of a pass-by areaconfiguration 715. FIGS. 13A and 13B illustrate dimensions of theexample implementation illustrated in FIG. 12A. The pass-by areaconfiguration can include multiple coplanar antenna panels 105 _(i). InFIGS. 12A and 13A-B, twelve coplanar panels 105 i are arranged in a 4 by3 arrangement, each panel 105 _(i) separated from a neighboring panel byinter-panel spacing 1305 and 1310 of between 4 and 8 centimeters,respectively. In FIGS. 12B and 12C, nine coplanar panels 105 _(i) arearranged in a 3 by 3 arrangement.

FIGS. 14 A-C illustrates several views of an access and chokepointconfiguration 720.

FIG. 14A is a cross-sectional diagram, FIG. 14B is a front view, andFIG. 14C is a side perspective view illustrating the access andchokepoint configuration. The configuration illustrated in FIG. 14A-Chas two posts, each post having two approach (or forward facing) panelsarranged vertically with respect to one another. Each grouping of twopanels is referred to as a set of panels. The approach panels in a givenset are substantially coplanar in a first plane (e.g., the face of thepanels have substantially parallel normal). A pass-through regionbetween the two posts (e.g., the first set of two approach panels andthe second set of approach panels) allows for inspection of individualsor other targets passing through the posts.

In some implementations, the angle of the first plane a as measured to atransverse axis 1405 can vary between 10 and 85 degrees. In an exampleimplementation, the angle α is 22 degrees. An angle of the second planecan similarly be between 10 and 85 degrees. Thus, an angle between thefirst plane and the second plane can be between 100 degrees and 170degrees, and in the example implementation, the angle between the firstplane and the second plane is 134 degrees. By controlling the angle ofthe antenna panels, the observation domain can be controlled.

Inter-panel spacing 1410 in the vertical direction can vary and in anexample implementation is 45.8 cm. Thus, with the example panelsdescribed above (in which each panel's vertical dimension is between 20and 30 centimeters) and in the access and chokepoint panelconfiguration, the two approach panels in a given set are separatedvertically by between 30 and 60 centimeters and span a vertical distanceless than 120 centimeters.

Referring again to FIG. 1, modular imaging system 100 can include dataacquisition system (DAS) panel 110 _(i) (i=1, 2, . . . , n) for eachantenna panel 105 _(i). DAS panel 110 _(i) digitizes raw RF datareceived from its associated antenna panel 105 _(i) and bundles the datafor transmission to a DAS base station 115. DAS base station 115receives the digitized raw RF data from each of the DAS panels 110 _(i),aggregates the received data, and transmits the aggregated data asin-phase and quadrature data to a processing system 120. In someimplementations, DAS base station 115 transmits data to processingsystem 120 via a universal serial bus (USB) 3.0 connection.

Modular imaging system 100 can include RF base 160 capable of generatingan RF local oscillator reference signal that can be distributed toantenna panels 105 _(i). In some implementations, the reference signalcan establish a fully phase coherent imaging system across allreceive-transmit antenna pairs and across all antenna panels 105 _(i).

Modular imaging system 100 can include sensor 125 such as an infrared(IR) camera, thermal camera, ultrasonic distance sensor, video camera,electro-optical (EO) camera, or surface/depth map camera. Sensor 125creates an additional information image or video, such as an opticalimage, of at least the OD 107. In some implementations, sensor 125transmits images or video via a USB connection to processing system 120for further analysis. The modular imaging system 100 can includemultiple sensors 125. Sensor 125 can also be used to detect for thepresence of a target in the OD 107. Detecting the presence of a targetedin the OD 107 can be used to trigger RF scanning by the imaging system100.

Processing system 120 includes a number of modules for processing radarreturn data and additional information images from sensor 125 of the OD107 including data acquisition process 130, calibration process 135,reconstruction process 140, automatic threat recognition process 145 andrenderer 150.

Data acquisition process 130 acquires raw data from the DAS base station115 and additional information images from the sensor 125. For eachsensor (e.g., antenna panel 105 _(i) and sensor 125), data acquisitionprocess 130 acquires and normalizes the sensor data. Timing of thesensor data is synchronized across sensors and data acquisition process130 publishes the acquired data as frames (e.g., time slices) forfurther analysis by modular imaging system 100. Thus, for a given frame,data acquisition process 130 publishes a set of data for each antennapanel 105 _(i) and sensor 125. In some implementations, data is acquiredand frames are published at near video frame rates (e.g., approximately24 frames per second).

Calibration process 135 applies calibration to the published data.

Reconstruction process 140 transforms the calibrated radar return datainto images and/or feature maps using compressed sensing constraints. Animage can be created for each antenna panel 105 _(i), and/or based on acomposite of measurements obtained by multiple antenna panels 105 _(i).Because measurements of the OD 107 are sparsely acquired via antennapanels 105 _(i), reconstructing an image of the OD 107 can be consideredas finding solutions to an underdetermined linear system. Compressedsensing is a signal processing technique for efficiently acquiring andreconstructing a signal (e.g., an image of the target residing in OD107), by finding solutions to underdetermined linear systems. Thesolution may be found using, e.g., matched-filter, least-squares, andlike solution algorithms. Compressed sensing is based on the principlethat, through optimization, the inherent information sparsity anda-priori knowledge of many features of that information when consideringone has knowledge of items or subjects that may occupy the OD can beexploited to recover the images of interest from far fewer samples thanrequired by the Shannon-Nyquist sampling theorem.

Image data from the sensor 125 can be used to further enforce thesparsity constraint beyond that supplied by a-priori knowledge of itemsor subjects that may occupy the OD. Specifically, an image of the OD 107acquired by sensor 125 can be used to determine a spatial location ofthe target (e.g., which voxels of the OD 107 the target resides in andwhich voxels of the OD 107 are empty). Empty voxels contain noscatterers and therefore can be considered zero for compressed sensingreconstruction (e.g., enabling better and/or quicker estimations of thesolution to the underdetermined linear system).

In addition, an appropriate sized OD 107 can result in a scene that issufficiently sparse for compressed sensing reconstruction. For example,if an OD 107 is a volume that is 2 meters by 1 meter by 0.5 meters, andis divided into 8,000,000 voxels of 5 mm, a typical human located withinthis OD 107 would occupy only about 10% of the voxels at any moment(e.g., approximately 800,000 voxels). An image from a sensor 125 can beused to determine three-dimensional surfaces within the OD 107 volumeand consequently which voxels the individual resides in. The emptyvoxels can be forced to zeros when reconstructing the radar return imagewhile non-zeroed voxels can be altered during reconstruction (e.g., canbe considered variables to find an optimal reconstructed solution to theunderdetermined linear system).

Reconstruction process 140 can reconstruct one or more images. Forexample, each panel can serve as a transmit/receive pair and can betreated independently. For N panels, there are N² independent “effectiveapertures,” each with a unique center-of-mass. Reconstruction process140 can reconstruct an image from each of these effective apertures. Inaddition, reconstruction process 140 can create aggregate images bycombining multiple independent images. In addition, reconstructionprocess can treat all panels as one large sparse aperture andreconstruct a single image using the information acquired from allpanels in the single aperture

Reconstruction process 140 can generate feature maps from thereconstructed images. Feature maps can include scatterer return data orother characterizations or features of the radar return measurements.Statistical analysis can be performed across multiple images. Someexample features include local surface normal, surface-width, surfacesmoothness/pointiness, summed magnitude, and the like. Other featuresare possible.

Automatic threat recognition process 145 analyzes radar return imagesand/or feature maps for presence of threat objects. Threat objects caninclude dangerous items that an individual may conceal on their person,for example, guns, knives, and explosives. Automatic threat recognitionprocess 145 may identify threats using, for example, a classifier thatassesses the feature maps generated by reconstruction process 140. Theclassifier may train on known threat images.

Renderer 150 generates or renders an image characterizing the outcome ofthe threat recognition 145 analysis. The image is rendered on display155. For example, renderer 150 can illustrate an avatar of a scannedperson and any identified threats. Renderer 150 can illustrate acharacterization that automatic threat recognition 145 did not detectany threats.

FIG. 5 is a processing block diagram illustrating processing steps 500of various components of the example modular imaging system 100. At 505,antenna panels 105 _(i) transmit and receive signals at operatingfrequencies between 24 and 29.5 GHz. The antenna panels 105 _(i) receiveraw RF radar returns. DAS boards 110 _(i) compares these returns againstthe reference Local Oscillator (transmitted signal) and digitizes thereturns to generate a complex valued (in-phase and quadrature), phasecoherent, digital data stream, at 510. In addition, DAS boards 110 _(i)relay in parallel, their respective digitized data stream to the DASbase station 115.

At 515, DAS base station 115 aggregates the digitized data from each ofthe DAS board 110 _(i). In the example implementation of the modularimaging system 100 shown in FIG. 1 and FIG. 5, the DAS base station 115can interface with up to 16 DAS boards 110 _(i), although in otherimplementations, the DAS base station 115 can interface with additionalDAS boards 110 _(i). DAS base station 115 transmits the aggregated datato processing system 120.

At 520, data acquisition process 130 receives the aggregated data fromDAS base station 115 and receives information images from sensor 125.Data acquisition process 130 synchronizes timing and publishes theacquired data in frames.

At 525, calibration process 135 applies calibration to the publisheddata on a sensor by sensor basis.

At 530, reconstruction process 140 applies compressed sensing solvingalgorithms to the calibrated data to reconstruct images and/or featuremaps. Reconstruction process 140 can reconstruct images for eachtransmit/receive pair of panels. In addition, reconstruction process 140can determine a spatial location of a target in the OD from the imagederived from sensor 125 and, based on the spatial location of thetarget, determine a sparsity constraint for use in the compressedsensing solving algorithms. Other sensors may yield other types of“constraints/priors” to aid the compressed sensing solving algorithms insimilar ways. In some implementations, the image derived from sensor 125is a surface map image or depth map image (e.g., generated by a surfacemap camera) that contains information relating to the distance of thesurfaces of scene objects from the sensor 125 viewpoint or anotherviewpoint.

At 535, automatic threat recognition process 145 analyzes the imagesand/or feature maps, for example, using a classifier, for the presenceof threat objects. An indication or characterization of the presence ofa threat object is provided to renderer 150, which, at 540 displays indisplay 150 the indication of the presence of the threat object on anavatar of the target in the OD 107.

FIG. 6 is a process flow diagram illustrating a process 600 ofconstructing a radar return image from data measured by a plurality ofantenna panels 105 _(i).

At 610, data characterizing radar returns are received. The radarreturns having been measured by a plurality of antenna panels 105 _(i)comprising an array of antenna elements including at least two antennaelements that are sparsely distributed on the antenna panel 105 _(i)(e.g., separated by a spacing more than a half wavelength of theoperating frequencies). The plurality of antenna panels 105 _(i) beingconfigurable to be arranged to measure a target in an observation, forexample, as described in the system of FIG. 1. The plurality of antennapanels 105 _(i) can be configurable to be spatially arranged andoriented with respect to one another based on an intended application.

At 620, data characterizing an image containing the OD is received. Theimage can be measured by a sensor 125 having a field of view overlappingwith the OD. The sensor 125 can include an infrared sensor,electro/optical sensor, surface map camera, and the like.

At 630, data characterizing the radar returns can be generated ascomplex, phase coherent (e.g., in-phase and quadrature) data. Thein-phase and quadrature data can be generated from the analog receptionof the RF signal at antenna panel 105 _(i) and by comparing the analogreception against a reference RF signal whose comparative result isrelayed to 110 _(i) were it is digitized.

At 640, a spatial location (for instance) of the target can bedetermined using the data characterizing the sensor image (other typesof information from other sensor may also be generated. The spatiallocation (or other information) of the target can define empty voxelsand occupied voxels (e.g., voxels in which the target is present) (orother priors) in the OD.

At 650, a radar return image of the target can be constructed using asparsity constraint determined from the spatial location of the target(or other priors from other sensors). The sparsity constraint caninclude considering empty voxels to have zero values for compressedsensing reconstruction algorithms. Feature maps may be generated and thepresence of threat objects in the OD may be detected for using theimages and/or feature maps. In some implementations, a characterizationof the detected threat objects may be displayed, for example, with anavatar of a person indicating the location of the threat object on theperson.

Although a few variations have been described in detail above, othermodifications or additions are possible. For example, the number ofantenna panels is not limited and some implementations may include anynumber of antenna panels, which may be configurable and/orreconfigurable based on the intended application. The antenna panels arenot limited to a particular frequency, for example, antenna panels withdifferent properties (operating frequencies, element locations, and thelike) can be used. In some implementations, an already implementedsystem can have the antenna panels swapped or exchanged for antennapanels and DAS panels with differing properties (operating frequencies,element locations, and the like). Different compressed sensingreconstruction algorithms may be used and different features may be usedfor threat detection. The OD may be a single continuous region ormultiple separate regions. Other implementations are possible.

Without in any way limiting the scope, interpretation, or application ofthe claims appearing below, a technical effect of one or more of theexample implementations disclosed herein may include one or more of thefollowing, for example, modular antenna panels can serve as buildingblocks to allow for optimal location. The location can be based onintended applications to better illuminate an individual being screenedand eliminate blind spots, which can improve probability of detectionwhile reducing false alarm rates. The modular antenna panels can besolid state and the system can have no moving parts, which increasesimage acquisition frame rates enabling walk-thru/walk-by and overt orcovert operation versus conventionally deployed mechanically scanningdevices, operational life and reduces maintenance costs. In someconfigurations, the modular antenna panels can screen individualswalking in near proximity, thereby eliminating the need for screenedindividuals to remain stationary during the imaging process. Compressedsensing can reduce the amount of data that is measured, which can reducethe amount of data processed, which can reduce system cost, requiredprocessing time, size (e.g., footprint), and the like. In addition, anynumber of modular antenna panels can be used, allowing the system toscale based on intended application. Additional antenna panels canimprove resolution, while fewer antenna panels can lower cost.

One or more aspects or features of the subject matter described hereincan be realized in digital electronic circuitry, integrated circuitry,specially designed application specific integrated circuits (ASICs),field programmable gate arrays (FPGAs) computer hardware, firmware,software, and/or combinations thereof. These various aspects or featurescan include implementation in one or more computer programs that areexecutable and/or interpretable on a programmable system including atleast one programmable processor, which can be special or generalpurpose, coupled to receive data and instructions from, and to transmitdata and instructions to, a storage system, at least one input device,and at least one output device. The programmable system or computingsystem may include clients and servers. A client and server aregenerally remote from each other and typically interact through acommunication network. The relationship of client and server arises byvirtue of computer programs running on the respective computers andhaving a client-server relationship to each other.

These computer programs, which can also be referred to as programs,software, software applications, applications, components, or code,include machine instructions for a programmable processor, and can beimplemented in a high-level procedural language, an object-orientedprogramming language, a functional programming language, a logicalprogramming language, and/or in assembly/machine language. As usedherein, the term “machine-readable medium” refers to any computerprogram product, apparatus and/or device, such as for example magneticdiscs, optical disks, memory, and Programmable Logic Devices (PLDs),used to provide machine instructions and/or data to a programmableprocessor, including a machine-readable medium that receives machineinstructions as a machine-readable signal. The term “machine-readablesignal” refers to any signal used to provide machine instructions and/ordata to a programmable processor. The machine-readable medium can storesuch machine instructions non-transitorily, such as for example as woulda non-transient solid-state memory or a magnetic hard drive or anyequivalent storage medium. The machine-readable medium can alternativelyor additionally store such machine instructions in a transient manner,such as for example as would a processor cache or other random accessmemory associated with one or more physical processor cores.

To provide for interaction with a user, one or more aspects or featuresof the subject matter described herein can be implemented on a computerhaving a display device, such as for example a cathode ray tube (CRT) ora liquid crystal display (LCD) or a light emitting diode (LED) monitorfor displaying information to the user and a keyboard and a pointingdevice, such as for example a mouse or a trackball, by which the usermay provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. For example, feedbackprovided to the user can be any form of sensory feedback, such as forexample visual feedback, auditory feedback, or tactile feedback; andinput from the user may be received in any form, including, but notlimited to, acoustic, speech, or tactile input. Other possible inputdevices include, but are not limited to, touch screens or othertouch-sensitive devices such as single or multi-point resistive orcapacitive trackpads, voice recognition hardware and software, opticalscanners, optical pointers, digital image capture devices and associatedinterpretation software, and the like.

In the descriptions above and in the claims, phrases such as “at leastone of” or “one or more of” may occur followed by a conjunctive list ofelements or features. The term “and/or” may also occur in a list of twoor more elements or features. Unless otherwise implicitly or explicitlycontradicted by the context in which it is used, such a phrase isintended to mean any of the listed elements or features individually orany of the recited elements or features in combination with any of theother recited elements or features. For example, the phrases “at leastone of A and B;” “one or more of A and B;” and “A and/or B” are eachintended to mean “A alone, B alone, or A and B together.” A similarinterpretation is also intended for lists including three or more items.For example, the phrases “at least one of A, B, and C;” “one or more ofA, B, and C;” and “A, B, and/or C” are each intended to mean “A alone, Balone, C alone, A and B together, A and C together, B and C together, orA and B and C together.” In addition, use of the term “based on,” aboveand in the claims is intended to mean, “based at least in part on,” suchthat an unrecited feature or element is also permissible.

The subject matter described herein can be embodied in systems,apparatus, methods, and/or articles depending on the desiredconfiguration. The implementations set forth in the foregoingdescription do not represent all implementations consistent with thesubject matter described herein. Instead, they are merely some examplesconsistent with aspects related to the described subject matter.Although a few variations have been described in detail above, othermodifications or additions are possible. In particular, further featuresand/or variations can be provided in addition to those set forth herein.For example, the implementations described above can be directed tovarious combinations and subcombinations of the disclosed featuresand/or combinations and subcombinations of several further featuresdisclosed above. In addition, the logic flows depicted in theaccompanying figures and/or described herein do not necessarily requirethe particular order shown, or sequential order, to achieve desirableresults. Other implementations may be within the scope of the followingclaims.

What is claimed is:
 1. A system comprising: a plurality of antennapanels comprising an array of antenna elements including at least twoantenna elements separated by a spacing more than a half wavelength, theplurality of antenna panels are configurable to be spatially arrangedand oriented with respect to one another to measure radar returns of anobservation volume for a target; an optical sensor having a field ofview overlapping the observation volume and for measuring an opticalimage; and at least one data processor forming part of at least onecomputing system and adapted to receive data characterizing the opticalimage and the radar returns, determine a spatial location of the targetusing the data characterizing the optical image, determine a sparsityconstraint using the determined spatial location of the target, andconstruct a radar return image of the target using the determinedsparsity constraint and the radar returns, wherein the spatial locationof the target defines empty voxels and voxels in which the target ispresent.
 2. The system of claim 1, further comprising: a base station toat least receive the radar returns from the plurality of antenna panelsand generate the data characterizing the radar returns as in-phase andquadrature data; a display; wherein the at least one data processorforming part of at least one computing system is further adapted todetect for a presence of threat objects in the radar return image; andwherein the at least one data processor forming part of the at least onecomputing system is further adapted to render, in the display,characterizations of the detected threat objects.
 3. The system of claim1, wherein the plurality of antenna panels are configurable to bespatially arranged and oriented with respect to one another based on anintended application.
 4. The system of claim 1, the plurality of antennapanels including: four approach panels arranged vertically with respectto one another and coplanar in a first plane; four rearward panelsarranged vertically with respect to one another and coplanar in a secondplane; wherein an angle between the first plane and the second plane isbetween 10 degrees and 170 degrees.
 5. The system of claim 4, whereinthe angle between the first plane and the second plane is between 60degrees and 120 degrees.
 6. The system of claim 4, wherein the fourapproach panels span a vertical distance less than 160 centimeters andeach panel's vertical dimension is between 20 and 30 centimeters.
 7. Thesystem of claim 5, the plurality of antenna panels further including: asecond set of four approach panels; and a second set of four rearwardpanels, with a pass-through region between the four approach panels andthe second set of approach panels.
 8. The system of claim 1, furthercomprising: a housing having a first hinge to fold the housing, thehousing coupled to the plurality of antenna panels, the plurality ofantenna panels including four panels coplanar in a first plane.
 9. Thesystem of claim 8, wherein the plurality of antennas further include afifth panel coupled to the housing with a second hinge.
 10. The systemof claim 8, wherein the system is collapsible by folding the housingusing the first hinge so that each panel in the plurality of antennapanels is enclosed by the housing.
 11. The system of claim 8, wherein,when the housing is in a closed position, a largest dimension of thehousing is less than 50 centimeters, and a second dimension of thehousing is between 27 centimeters and 40 centimeters.
 12. The system ofclaim 1, the plurality of antenna panels including at least ninecoplanar panels in a row and column arrangement, each panel separatedfrom a neighboring panel by between 4 and 8 centimeters.
 13. The systemof claim 1, the plurality of antenna panels including: a first set oftwo approach panels arranged vertically with respect to one another andcoplanar in a first plane; a second set of two approach panels arrangedvertically with respect to one another and coplanar in a second plane;wherein an angle between the first plane and the second plane is between100 and 170 degrees.
 14. The system of claim 13, wherein the twoapproach panels in the first set are separated vertically by between 30and 60 centimeters.
 15. A method comprising: receiving, by at least onedata processor, data characterizing radar returns measured by aplurality of antenna panels comprising an array of antenna elementsincluding at least two antenna elements separated by a spacing more thana half wavelength, the plurality of antenna panels are configurable tobe spatially arranged and oriented with respect to one another tomeasure radar returns of an observation volume for a target; receiving,by at least one data processor, data characterizing an optical imagecontaining the observation volume and measured by an optical sensorhaving a field of view overlapping with the observation volume;determining a spatial location of the target using the datacharacterizing the optical image; determining a sparsity constraintusing the determined spatial location of the target; and constructing aradar return image of the target using the determined sparsityconstraint and the radar returns, wherein the spatial location of thetarget defines empty voxels and voxels in which the target is present.16. The method of claim 15, further comprising: generating, by a basestation receiving the radar returns from the plurality of antennapanels, the data characterizing the radar returns as in-phase andquadrature data; automatically detecting for a presence of threatobjects in the radar return image; and rendering, in a display,characterizations of the detected threat objects.
 17. The method ofclaim 15, wherein the plurality of antenna panels are configurable to bespatially arranged vertically adjacent to one another to inspect targetsmoving through the observation volume.
 18. A non-transitory computerprogram product which, when executed by at least one data processorforming part of at least one computer, result in operations comprising:receiving, by at least one data processor, data characterizing radarreturns measured by a plurality of antenna panels comprising an array ofantenna elements including at least two antenna elements separated by aspacing more than a half wavelength, the plurality of antenna panels areconfigurable to be spatially arranged and oriented with respect to oneanother to measure radar returns of an observation volume for a target;receiving, by at least one data processor, data characterizing anoptical image containing the observation volume and measured by anoptical sensor having a field of view overlapping with the observationvolume; determining a spatial location of the target using the datacharacterizing the optical image; determining a sparsity constraintusing the determined spatial location of the target; and constructing aradar return image of the target using the determined sparsityconstraint and the radar returns, wherein the spatial location of thetarget defines empty voxels and voxels in which the target is present.19. The non-transitory computer program product of claim 18, theoperations further comprising: generating, by a base station receivingthe radar returns from the plurality of antenna panels, the datacharacterizing the radar returns as in-phase and quadrature data;automatically detecting for a presence of threat objects in the radarreturn image; and rendering, in a display, characterizations of thedetected threat objects.
 20. The system of claim 1, wherein constructingthe radar return image includes solving an underdetermined linear systemusing compressed sensing.
 21. The system of claim 1, the at least onedata processor further adapted to determine three dimensional surfaceswithin the observation volume.